Integrating Species Distribution Models, GeoAI, and Citizen Science: Predictive Tools for Bird Habitat Assessment and Conservation Decision-Making

Bird populations are facing unprecedented global pressures from climate change, habitat fragmentation, land use transformation, and intensifying human activity. These threats are compounding rapidly, demanding tools that can process large, heterogeneous spatiotemporal datasets and translate scientific insight into effective conservation outcomes. Species distribution models (SDMs), geospatial artificial intelligence (GeoAI), remote sensing, and citizen science platforms such as eBird and iNaturalist have each advanced significantly in recent years, creating an opportunity to integrate these approaches into a coherent framework for bird habitat assessment and conservation planning.Despite this progress, the gap between predictive modelling and on-the-ground management decisions remains wide. Habitat suitability maps are rarely paired with quality assessments or connectivity analyses. Migration route predictions seldom account for real-time environmental dynamics or collision risk in human-modified landscapes. Conservation planning and reserve design still depend heavily on static data, even as the spatiotemporal dynamics and drivers of climate and land use change reshape ecosystems at pace.This Research Topic invites original contributions that advance the theory and practical application of predictive and spatial tools across the full spectrum of avian habitat science and conservation management. We are particularly interested in research that bridges the methodological and applied dimensions, from data-intensive modelling to actionable strategies for threatened and migratory species.We especially welcome submissions on the following topics:1. Species distribution and habitat suitability modelling2. GeoAI and machine learning for avian spatial analysis3. Remote sensing, LiDAR, and GIS for bird habitat mapping4. Citizen science data integration for predictive modelling5. Acoustic monitoring and computer vision with geospatial data6. Migration dynamics, flyway modelling, and collision risk assessment7. Spatiotemporal dynamics and drivers of climate and land use change impacts8. Landscape connectivity and habitat quality assessment9. Conservation prioritization, reserve design, and ecological restoration10. Adaptive management strategies for threatened and migratory species Topic editors: Kui Yang, Rong Fan, Sanjo Jose Veliyathukudy, Debanjan Sarkar, Alexandre Delplanque Source: https://www.frontiersin.org/research-topics/82591/integrating-species-distribution-models-geoai-and-citizen-science-predictive-tools-for-bird-habitat-assessment-and-conservation-decision-making